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Secure & Responsible AI: Agentic AI

The first instalment of our quarterly webinars on Secure & Responsible AI - Agentic AI. Learn how Large Language Models are evolving into the next wave of AI Agents—and why this shift is reshaping the future of software, business, and the web itself.

Responsible AI Reference Architecture

To be effective, the deployment of AI in enterprises needs to be carried out in a responsible manner, ensuring safety for users and the business, and security of the models and datasets. An AI Reference Architecture can identify and categorise the services required for a safe and secure environment for AI.

Architecting Agentic AI Semantic Conventions

By projecting the semantic conventions of Agentic AI, a layered architecture can be easily developed, and by mapping this to the SABSA Governance Framework an Agentic AI Governance model emerges.

AI Readiness Assessment

Take a strategic look at your ability to adopt and benefit from AI deployment and provide key insights into the organisational capability and understanding of what is required to effectively manage AI with our free online AI Readiness Self-Assessment.

Architecting Information for AI

The recent emergence of AI into the consumer, business, and government space has introduced not just new demands on access to data, but a whole new industry around data science in order to build AI models that can reason using plain language.  As architects we must ensure that whatever emerges from data science architected and aligned with business requirements in order to contribute value. 

TACO – Integrating Control Objectives for AI

The emergence of AI as a disruptive technology has spurred the development of standards and guidelines for the AI safety, security and responsible management but these do not align readily and an architectural model is required. Integrating these requirements in a Trusted AI Control Objectives (TACO) model supports an integrated compliance approach.